Reducing motion vector information transmission in bi-directional temporal prediction

ABSTRACT

A method for inter-coding video is provided in which transmission bandwidth requirements associated with second motion vectors for bi-directional temporal prediction is reduced. In the method motion vector information for only one of the two motion vectors for bi-directional temporal prediction can be transmitted together with information on how to derive or construct the second motion vector. Thus, rather than sending express information regarding two motion vectors, express information related to only one motion vector along with information related to reconstruction/derivation of the second motion vector is transmitted, thus reducing bandwidth requirements and increasing coding efficiency.

CLAIM OF PRIORITY

This application is a continuation of U.S. patent application Ser. No.16/377,833, filed Apr. 8, 2019, and this application claims priorityunder 35 U.S.C. § 119(e) from earlier filed U.S. Provisional ApplicationNo. 62/654,073, filed Apr. 6, 2018, and U.S. Provisional PatentApplication No. 62/656,114, filed Apr. 11, 2018, the entireties of eachof which are hereby incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to the field of video coding,particularly coding efficiency increases associated with reduction intransmission of motion vector information for Bi-directional temporalprediction.

BACKGROUND

The technical improvements in evolving video coding standards illustratethe trend of increasing coding efficiency to enable higher bit-rates,higher resolutions, and better video quality. The Joint VideoExploration Team developed a new video coding scheme referred to as JVETand is developing a newer video coding scheme referred to a VersatileVideo Coding (VVC)—the complete contents of the VVC 7^(th) edition ofdraft 2 of the standard titled Versatile Video Coding (Draft 2) by JVETpublished Oct. 1, 2018 is hereby incorporated herein by reference.Similar to other video coding schemes like HEVC (High Efficiency VideoCoding), both JVET and VVC are block-based hybrid spatial and temporalpredictive coding schemes. However, relative to HEVC, JVET and VVCinclude many modifications to bitstream structure, syntax, constraints,and mapping for the generation of decoded pictures. JVET has beenimplemented in Joint Exploration Model (JEM) encoders and decoders, butVVC is not anticipated to be implemented until early 2020.

Various coding techniques require that two motion vectors be using inthe reconstruction of a coding unit. Transmission of completeinformation related to the two motion vectors is inefficient andconsumes unnecessary bandwidth. What is needed is a system and method ofreducing overhead and burden associated with coding involving multipleMotion Vectors (MVs).

SUMMARY

A system of one or more computers can be configured to performparticular operations or actions by virtue of having software, firmware,hardware, or a combination of them installed on the system that inoperation causes or cause the system to perform the actions. One or morecomputer programs can be configured to perform particular operations oractions by virtue of including instructions that, when executed by dataprocessing apparatus, cause the apparatus to perform the actions. Onegeneral aspect comprises receiving information regarding a coding unit;determining motion information associated with said coding unit;determining whether more than one motion vector is associated with saidmotion information; determining a relationship between a first motionvector and a second motion vector if it is determined that said motioninformation is associated with more than one motion vector; and encodingsaid coding unit, where said coding unit includes information related tosaid first motion vector and information related to said relationshipbetween said first motion vector and said second motion vector. Otherembodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methods.

Implementations can comprise one or more of the following features: Themethod of inter-coding where said information related to saidrelationship between said first motion vector and said second motionvector includes information sufficient to reconstruct an MVP index andan MVD of said second motion vector; the method of inter-coding wheresaid information related to said relationship between said first motionvector and said second motion vector includes a scaling factor; themethod of inter-coding where said information related to saidrelationship between said first motion vector and said second motionvector includes information sufficient to reconstruct an MVP index andan MVD of said second motion vector; the method of inter-coding wheresaid information related to said relationship between said first motionvector and said second motion vector includes information regarding areference slice; the method of inter-coding where said informationrelated to said relationship between said first motion vector and saidsecond motion vector indicates said second motion vector is a mirrorimage of said first motion vector; the method of inter-coding where saidinformation related to said relationship between said first motionvector and said second motion vector includes reference indexinformation; the method of inter-coding where said information relatedto said relationship between said first motion vector and said secondmotion vector includes a control point for said second motion vector.Implementations of the described techniques can comprise hardware, amethod or process, or computer software on a computer-accessible medium.

Some embodiments can include a system of inter-coding comprising:receiving in a first memory information regarding a coding unit,determining motion information associated with said coding unit,determining whether more than one motion vector is associated with saidmotion information, determining a relationship between a first motionvector and a second motion vector if it is determined that said motioninformation is associated with more than one motion vector, and encodingsaid coding unit, where said coding unit includes information related tosaid first motion vector and information related to said relationshipbetween said first motion vector and said second motion vector. Otherembodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methods.

BRIEF DESCRIPTION OF THE DRAWINGS

Further details of the present invention are explained with the help ofthe attached drawings in which:

FIG. 1 depicts division of a frame into a plurality of Coding Tree Units(CTUs).

FIG. 2a-2c depict exemplary partitioning of a CTU into Coding Units(CUs).

FIG. 3 depicts a quadtree plus binary tree (QTBT) representation of FIG.2's CU partitioning.

FIG. 4 depicts a simplified block diagram for CU coding in a JVET or VVCencoder.

FIG. 5 depicts possible intra prediction modes for luma components inJVET of VVC.

FIG. 6 depicts a simplified block diagram for CU coding in a JVET of VVCdecoder.

FIG. 7 depicts a block diagram of a reduced-overhead encoding method foruse in encoding video.

FIG. 8 depicts a block diagram of a reduced-overhead decoding method foruse in decoding video.

FIG. 9 depicts an embodiment of a computer system adapted and configuredto provide for variable template size for template matching.

FIG. 10 depicts an embodiment of video encoder/decoder adapted andconfigured to provide for variable template size for template matching.

DETAILED DESCRIPTION

FIG. 1 depicts division of a frame into a plurality of Coding Tree Units(CTUs) 100. A frame can be an image in a video sequence. A frame caninclude a matrix, or set of matrices, with pixel values representingintensity measures in the image. Thus, a set of these matrices cangenerate a video sequence. Pixel values can be defined to representcolor and brightness in full color video coding, where pixels aredivided into three channels. For example, in a YCbCr color space pixelscan have a luma value, Y, that represents gray level intensity in theimage, and two chrominance values, Cb and Cr, that represent the extentto which color differs from gray to blue and red. In other embodiments,pixel values can be represented with values in different color spaces ormodels. The resolution of the video can determine the number of pixelsin a frame. A higher resolution can mean more pixels and a betterdefinition of the image, but can also lead to higher bandwidth, storage,and transmission requirements.

Frames of a video sequence can be encoded and decoded using JVET. JVETis a video coding scheme being developed by the Joint Video ExplorationTeam. Versions of JVET have been implemented in JEM (Joint ExplorationModel) encoders and decoders. Similar to other video coding schemes likeHEVC (High Efficiency Video Coding), JVET is a block-based hybridspatial and temporal predictive coding scheme. During coding with JVET,a frame is first divided into square blocks called CTUs 100, as shown inFIG. 1. For example, CTUs 100 can be blocks of 128×128 pixels.

FIG. 2a depicts an exemplary partitioning of a CTU 100 into CUs 102.Each CTU 100 in a frame can be partitioned into one or more CUs (CodingUnits) 102. CUs 102 can be used for prediction and transform asdescribed below. Unlike HEVC, in JVET the CUs 102 can be rectangular orsquare and can be coded without further partitioning into predictionunits or transform units. The CUs 102 can be as large as their root CTUs100, or be smaller subdivisions of a root CTU 100 as small as 4×4blocks.

In JVET, a CTU 100 can be partitioned into CUs 102 according to aquadtree plus binary tree (QTBT) scheme in which the CTU 100 can berecursively split into square blocks according to a quadtree, and thosesquare blocks can then be recursively split horizontally or verticallyaccording to binary trees. Parameters can be set to control splittingaccording to the QTBT, such as the CTU size, the minimum sizes for thequadtree and binary tree leaf nodes, the maximum size for the binarytree root node, and the maximum depth for the binary trees. In VVC, aCTU 100 can be portioned into CUs utilizing ternary splitting also.

By way of a non-limiting example, FIG. 2a shows a CTU 100 partitionedinto CUs 102, with solid lines indicating quadtree splitting and dashedlines indicating binary tree splitting. As illustrated, the binarysplitting allows horizontal splitting and vertical splitting to definethe structure of the CTU and its subdivision into CUs. FIGS. 2b & 2 cdepict alternate, non-limiting examples of ternary splitting of a CUwherein subdivisions of the CUs are non-equal.

FIG. 3 depicts a QTBT representation of FIG. 2's partitioning. Aquadtree root node represents the CTU 100, with each child node in thequadtree portion representing one of four square blocks split from aparent square block. The square blocks represented by the quadtree leafnodes can then be divided zero or more times using binary trees, withthe quadtree leaf nodes being root nodes of the binary trees. At eachlevel of the binary tree portion, a block can be divided eithervertically or horizontally. A flag set to “0” indicates that the blockis split horizontally, while a flag set to “1” indicates that the blockis split vertically.

After quadtree splitting and binary tree splitting, the blocksrepresented by the QTBT's leaf nodes represent the final CUs 102 to becoded, such as coding using inter prediction or intra prediction. Forslices or full frames coded with inter prediction, differentpartitioning structures can be used for luma and chroma components. Forexample, for an inter slice a CU 102 can have Coding Blocks (CBs) fordifferent color components, such as such as one luma CB and two chromaCBs. For slices or full frames coded with intra prediction, thepartitioning structure can be the same for luma and chroma components.

FIG. 4 depicts a simplified block diagram for CU coding in a WETencoder. The main stages of video coding include partitioning toidentify CUs 102 as described above, followed by encoding CUs 102 usingprediction at 404 or 406, generation of a residual CU 410 at 408,transformation at 412, quantization at 416, and entropy coding at 420.The encoder and encoding process illustrated in FIG. 4 also includes adecoding process that is described in more detail below.

Given a current CU 102, the encoder can obtain a prediction CU 402either spatially using intra prediction at 404 or temporally using interprediction at 406. The basic idea of prediction coding is to transmit adifferential, or residual, signal between the original signal and aprediction for the original signal. At the receiver side, the originalsignal can be reconstructed by adding the residual and the prediction,as will be described below. Because the differential signal has a lowercorrelation than the original signal, fewer bits are needed for itstransmission.

A slice, such as an entire picture or a portion of a picture, codedentirely with intra-predicted CUs can be an I slice that can be decodedwithout reference to other slices, and as such can be a possible pointwhere decoding can begin. A slice coded with at least someinter-predicted CUs can be a predictive (P) or bi-predictive (B) slicethat can be decoded based on one or more reference pictures. P slicesmay use intra-prediction and inter-prediction with previously codedslices. For example, P slices may be compressed further than theI-slices by the use of inter-prediction, but need the coding of apreviously coded slice to code them. B slices can use data from previousand/or subsequent slices for its coding, using intra-prediction orinter-prediction using an interpolated prediction from two differentframes, thus increasing the accuracy of the motion estimation process.In some cases P slices and B slices can also or alternately be encodedusing intra block copy, in which data from other portions of the sameslice is used.

As will be discussed below, intra prediction or inter prediction can beperformed based on reconstructed CUs 434 from previously coded CUs 102,such as neighboring CUs 102 or CUs 102 in reference pictures.

When a CU 102 is coded spatially with intra prediction at 404, an intraprediction mode can be found that best predicts pixel values of the CU102 based on samples from neighboring CUs 102 in the picture.

When coding a CU's luma component, the encoder can generate a list ofcandidate intra prediction modes. While HEVC had 35 possible intraprediction modes for luma components, in JVET there are 67 possibleintra prediction modes for luma components and in VVC there are 85prediction modes. These include a planar mode that uses a threedimensional plane of values generated from neighboring pixels, a DC modethat uses values averaged from neighboring pixels, the 65 directionalmodes shown in FIG. 5 that use values copied from neighboring pixelsalong the solid-line indicated directions and 18 wide-angle predictionmodes that can be used with non-square blocks.

When generating a list of candidate intra prediction modes for a CU'sluma component, the number of candidate modes on the list can depend onthe CU's size. The candidate list can include: a subset of HEVC's 35modes with the lowest SATD (Sum of Absolute Transform Difference) costs;new directional modes added for JVET that neighbor the candidates foundfrom the HEVC modes; and modes from a set of six most probable modes(MPMs) for the CU 102 that are identified based on intra predictionmodes used for previously coded neighboring blocks as well as a list ofdefault modes.

When coding a CU's chroma components, a list of candidate intraprediction modes can also be generated. The list of candidate modes caninclude modes generated with cross-component linear model projectionfrom luma samples, intra prediction modes found for luma CBs inparticular collocated positions in the chroma block, and chromaprediction modes previously found for neighboring blocks. The encodercan find the candidate modes on the lists with the lowest ratedistortion costs, and use those intra prediction modes when coding theCU's luma and chroma components. Syntax can be coded in the bitstreamthat indicates the intra prediction modes used to code each CU 102.

After the best intra prediction modes for a CU 102 have been selected,the encoder can generate a prediction CU 402 using those modes. When theselected modes are directional modes, a 4-tap filter can be used toimprove the directional accuracy. Columns or rows at the top or leftside of the prediction block can be adjusted with boundary predictionfilters, such as 2-tap or 3-tap filters.

The prediction CU 402 can be smoothed further with a position dependentintra prediction combination (PDPC) process that adjusts a prediction CU402 generated based on filtered samples of neighboring blocks usingunfiltered samples of neighboring blocks, or adaptive reference samplesmoothing using 3-tap or 5-tap low pass filters to process referencesamples.

When a CU 102 is coded temporally with inter prediction at 406, a set ofmotion vectors (MVs) can be found that points to samples in referencepictures that best predict pixel values of the CU 102. Inter predictionexploits temporal redundancy between slices by representing adisplacement of a block of pixels in a slice. The displacement isdetermined according to the value of pixels in previous or followingslices through a process called motion compensation. Motion vectors andassociated reference indices that indicate pixel displacement relativeto a particular reference picture can be provided in the bitstream to adecoder, along with the residual between the original pixels and themotion compensated pixels. The decoder can use the residual and signaledmotion vectors and reference indices to reconstruct a block of pixels ina reconstructed slice.

In JVET, motion vector accuracy can be stored at 1/16 pel, and thedifference between a motion vector and a CU's predicted motion vectorcan be coded with either quarter-pel resolution or integer-pelresolution.

In JVET motion vectors can be found for multiple sub-CUs within a CU102, using techniques such as advanced temporal motion vector prediction(ATMVP), spatial-temporal motion vector prediction (STMVP), affinemotion compensation prediction, pattern matched motion vector derivation(PMMVD), and/or bi-directional optical flow (BIO).

Using ATMVP, the encoder can find a temporal vector for the CU 102 thatpoints to a corresponding block in a reference picture. The temporalvector can be found based on motion vectors and reference pictures foundfor previously coded neighboring CUs 102. Using the reference blockpointed to by a temporal vector for the entire CU 102, a motion vectorcan be found for each sub-CU within the CU 102.

STMVP can find motion vectors for sub-CUs by scaling and averagingmotion vectors found for neighboring blocks previously coded with interprediction, together with a temporal vector.

Affine motion compensation prediction can be used to predict a field ofmotion vectors for each sub-CU in a block, based on two control motionvectors found for the top corners of the block. For example, motionvectors for sub-CUs can be derived based on top corner motion vectorsfound for each 4×4 block within the CU 102.

PMMVD can find an initial motion vector for the current CU 102 usingbilateral matching or template matching. Bilateral matching can look atthe current CU 102 and reference blocks in two different referencepictures along a motion trajectory, while template matching can look atcorresponding blocks in the current CU 102 and a reference pictureidentified by a template. The initial motion vector found for the CU 102can then be refined individually for each sub-CU.

BIO can be used when inter prediction is performed with bi-predictionbased on earlier and later reference pictures, and allows motion vectorsto be found for sub-CUs based on the gradient of the difference betweenthe two reference pictures.

In some situations local illumination compensation (LIC) can be used atthe CU level to find values for a scaling factor parameter and an offsetparameter, based on samples neighboring the current CU 102 andcorresponding samples neighboring a reference block identified by acandidate motion vector. In JVET, the LIC parameters can change and besignaled at the CU level.

For some of the above methods the motion vectors found for each of aCU's sub-CUs can be signaled to decoders at the CU level. For othermethods, such as PMMVD and BIO, motion information is not signaled inthe bitstream to save overhead, and decoders can derive the motionvectors through the same processes.

After the motion vectors for a CU 102 have been found, the encoder cangenerate a prediction CU 402 using those motion vectors. In some cases,when motion vectors have been found for individual sub-CUs, OverlappedBlock Motion Compensation (OBMC) can be used when generating aprediction CU 402 by combining those motion vectors with motion vectorspreviously found for one or more neighboring sub-CUs.

When bi-prediction is used, JVET can use decoder-side motion vectorrefinement (DMVR) to find motion vectors. DMVR allows a motion vector tobe found based on two motion vectors found for bi-prediction using abilateral template matching process. In DMVR, a weighted combination ofprediction CUs 402 generated with each of the two motion vectors can befound, and the two motion vectors can be refined by replacing them withnew motion vectors that best point to the combined prediction CU 402.The two refined motion vectors can be used to generate the finalprediction CU 402.

At 408, once a prediction CU 402 has been found with intra prediction at404 or inter prediction at 406 as described above, the encoder cansubtract the prediction CU 402 from the current CU 102 find a residualCU 410.

The encoder can use one or more transform operations at 412 to convertthe residual CU 410 into transform coefficients 414 that express theresidual CU 410 in a transform domain, such as using a discrete cosineblock transform (DCT-transform) to convert data into the transformdomain. JVET allows more types of transform operations than HEVC,including DCT-II, DST-VII, DST-VII, DCT-VIII, DST-I, and DCT-Voperations. The allowed transform operations can be grouped intosub-sets, and an indication of which sub-sets and which specificoperations in those sub-sets were used can be signaled by the encoder.In some cases, large block-size transforms can be used to zero out highfrequency transform coefficients in CUs 102 larger than a certain size,such that only lower-frequency transform coefficients are maintained forthose CUs 102.

In some cases a mode dependent non-separable secondary transform(MDNSST) can be applied to low frequency transform coefficients 414after a forward core transform. The MDNSST operation can use aHypercube-Givens Transform (HyGT) based on rotation data. When used, anindex value identifying a particular MDNSST operation can be signaled bythe encoder.

At 416, the encoder can quantize the transform coefficients 414 intoquantized transform coefficients 416. The quantization of eachcoefficient may be computed by dividing a value of the coefficient by aquantization step, which is derived from a quantization parameter (QP).In some embodiments, the Qstep is defined as 2^((QP−4)/6). Because highprecision transform coefficients 414 can be converted into quantizedtransform coefficients 416 with a finite number of possible values,quantization can assist with data compression. Thus, quantization of thetransform coefficients may limit an amount of bits generated and sent bythe transformation process. However, while quantization is a lossyoperation, and the loss by quantization cannot be recovered, thequantization process presents a trade-off between quality of thereconstructed sequence and an amount of information needed to representthe sequence. For example, a lower QP value can result in better qualitydecoded video, although a higher amount of data may be required forrepresentation and transmission. In contrast, a high QP value can resultin lower quality reconstructed video sequences but with lower data andbandwidth needs.

JVET can utilize variance-based adaptive quantization techniques, whichallows every CU 102 to use a different quantization parameter for itscoding process (instead of using the same frame QP in the coding ofevery CU 102 of the frame). The variance-based adaptive quantizationtechniques adaptively lowers the quantization parameter of certainblocks while increasing it in others. To select a specific QP for a CU102, the CU's variance is computed. In brief, if a CU's variance ishigher than the average variance of the frame, a higher QP than theframe's QP may be set for the CU 102. If the CU 102 presents a lowervariance than the average variance of the frame, a lower QP may beassigned.

At 420, the encoder can find final compression bits 422 by entropycoding the quantized transform coefficients 418. Entropy coding aims toremove statistical redundancies of the information to be transmitted. InJVET, CABAC (Context Adaptive Binary Arithmetic Coding) can be used tocode the quantized transform coefficients 418, which uses probabilitymeasures to remove the statistical redundancies. For CUs 102 withnon-zero quantized transform coefficients 418, the quantized transformcoefficients 418 can be converted into binary. Each bit (“bin”) of thebinary representation can then be encoded using a context model. A CU102 can be broken up into three regions, each with its own set ofcontext models to use for pixels within that region.

Multiple scan passes can be performed to encode the bins. During passesto encode the first three bins (bin0, bin1, and bin2), an index valuethat indicates which context model to use for the bin can be found byfinding the sum of that bin position in up to five previously codedneighboring quantized transform coefficients 418 identified by atemplate.

A context model can be based on probabilities of a bin's value being ‘0’or ‘1’. As values are coded, the probabilities in the context model canbe updated based on the actual number of ‘0’ and ‘1’ values encountered.While HEVC used fixed tables to re-initialize context models for eachnew picture, in WET the probabilities of context models for newinter-predicted pictures can be initialized based on context modelsdeveloped for previously coded inter-predicted pictures.

The encoder can produce a bitstream that contains entropy encoded bits422 of residual CUs 410, prediction information such as selected intraprediction modes or motion vectors, indicators of how the CUs 102 werepartitioned from a CTU 100 according to the QTBT structure, and/or otherinformation about the encoded video. The bitstream can be decoded by adecoder as discussed below.

In addition to using the quantized transform coefficients 418 to findthe final compression bits 422, the encoder can also use the quantizedtransform coefficients 418 to generate reconstructed CUs 434 byfollowing the same decoding process that a decoder would use to generatereconstructed CUs 434. Thus, once the transformation coefficients havebeen computed and quantized by the encoder, the quantized transformcoefficients 418 may be transmitted to the decoding loop in the encoder.After quantization of a CU's transform coefficients, a decoding loopallows the encoder to generate a reconstructed CU 434 identical to theone the decoder generates in the decoding process. Accordingly, theencoder can use the same reconstructed CUs 434 that a decoder would usefor neighboring CUs 102 or reference pictures when performing intraprediction or inter prediction for a new CU 102. Reconstructed CUs 102,reconstructed slices, or full reconstructed frames may serve asreferences for further prediction stages.

At the encoder's decoding loop (and see below, for the same operationsin the decoder) to obtain pixel values for the reconstructed image, adequantization process may be performed. To dequantize a frame, forexample, a quantized value for each pixel of a frame is multiplied bythe quantization step, e.g., (Qstep) described above, to obtainreconstructed dequantized transform coefficients 426. For example, inthe decoding process shown in FIG. 4 in the encoder, the quantizedtransform coefficients 418 of a residual CU 410 can be dequantized at424 to find dequantized transform coefficients 426. If an MDNSSToperation was performed during encoding, that operation can be reversedafter dequantization.

At 428, the dequantized transform coefficients 426 can be inversetransformed to find a reconstructed residual CU 430, such as by applyinga DCT to the values to obtain the reconstructed image. At 432 thereconstructed residual CU 430 can be added to a corresponding predictionCU 402 found with intra prediction at 404 or inter prediction at 406, inorder to find a reconstructed CU 434.

At 436, one or more filters can be applied to the reconstructed dataduring the decoding process (in the encoder or, as described below, inthe decoder), at either a picture level or CU level. For example, theencoder can apply a deblocking filter, a sample adaptive offset (SAO)filter, and/or an adaptive loop filter (ALF). The encoder's decodingprocess may implement filters to estimate and transmit to a decoder theoptimal filter parameters that can address potential artifacts in thereconstructed image. Such improvements increase the objective andsubjective quality of the reconstructed video. In deblocking filtering,pixels near a sub-CU boundary may be modified, whereas in SAO, pixels ina CTU 100 may be modified using either an edge offset or band offsetclassification. WET's ALF can use filters with circularly symmetricshapes for each 2×2 block. An indication of the size and identity of thefilter used for each 2×2 block can be signaled.

If reconstructed pictures are reference pictures, they can be stored ina reference buffer 438 for inter prediction of future CUs 102 at 406.

During the above steps, JVET allows a content adaptive clippingoperations to be used to adjust color values to fit between lower andupper clipping bounds. The clipping bounds can change for each slice,and parameters identifying the bounds can be signaled in the bitstream.

FIG. 6 depicts a simplified block diagram for CU coding in a JVETdecoder. A JVET decoder can receive a bitstream containing informationabout encoded CUs 102. The bitstream can indicate how CUs 102 of apicture were partitioned from a CTU 100 according to a QTBT structure,prediction information for the CUs 102 such as intra prediction modes ormotion vectors, and bits 602 representing entropy encoded residual CUs.

At 604 the decoder can decode the entropy encoded bits 602 using theCABAC context models signaled in the bitstream by the encoder. Thedecoder can use parameters signaled by the encoder to update the contextmodels' probabilities in the same way they were updated during encoding.

After reversing the entropy encoding at 604 to find quantized transformcoefficients 606, the decoder can dequantize them at 608 to finddequantized transform coefficients 610. If an MDNSST operation wasperformed during encoding, that operation can be reversed by the decoderafter dequantization.

At 612, the dequantized transform coefficients 610 can be inversetransformed to find a reconstructed residual CU 614. At 616, thereconstructed residual CU 614 can be added to a corresponding predictionCU 626 found with intra prediction at 622 or inter prediction at 624, inorder to find a reconstructed CU 618.

At 620, one or more filters can be applied to the reconstructed data, ateither a picture level or CU level. For example, the decoder can apply adeblocking filter, a sample adaptive offset (SAO) filter, and/or anadaptive loop filter (ALF). As described above, the in-loop filterslocated in the decoding loop of the encoder may be used to estimateoptimal filter parameters to increase the objective and subjectivequality of a frame. These parameters are transmitted to the decoder tofilter the reconstructed frame at 620 to match the filteredreconstructed frame in the encoder.

After reconstructed pictures have been generated by findingreconstructed CUs 618 and applying signaled filters, the decoder canoutput the reconstructed pictures as output video 628. If reconstructedpictures are to be used as reference pictures, they can be stored in areference buffer 630 for inter prediction of future CUs 102 at 624.

Bi-directional temporal prediction employs two MVs referring toreference slices in two reference lists to determine two predictionblocks. These two prediction blocks are then combined to form finalprediction block. In JVET and VVC, several inter coding modes (skip,merge, FRUC, AMVP, AFFINE) include bi-directional temporal prediction toincreased prediction accuracy. Signaling for the two MVs varies by thecoding mode. AMVP (Advanced MV Predictor) utilizes the most flexiblesignaling for the two MVs. Specifically, three information types arerequired to generate MV; reference index, MVP index, and MVD. Hence, acoding block using AMVP with bi-directional temporal prediction mustsend two reference indices, two MVP indices, and two MVDs.

The affine motion model describes motion between two frames in a moreflexible way, such as rotation, shear and scale. The affine modelemploys an affine transformation to describe motion based on modelparameters. In JVET and VVC, four or six parameter models can beemployed. Instead of using affine motion model to compute motion fieldfor each pixel in coding block, JVET and VVC can compute MV at a coarsergranularity, such as a block of size 4×4. Moreover, JVET and VVCdescribe an affine motion model of a coding block through control pointmotion vectors. That is, MV for each block coding using affine mode canbe determined based on control point motion vectors.

Control point MVs can be coded using predictive coding in a similarfashion as normal MV in JVET and VVC. MV predictors for each controlpoint MV are first determined and then MV a difference between the MVpredictor and the control point MV can then be coded and signaled in thebitstream. That is, two control point MVs can be used for afour-parameter Affine model and three control point MVs can be used fora six-parameter Affine model.

Bi-directional temporal prediction using Affine motion model requiresadditional overhead to signal additional control point MV. For fourparameter Affine model, two MVDs are signaled for each list, instead ofone. Similarly, three MVDs are signaled for each list, instead of one,when size parameter Affine model is used. Hence, a coding block usingAffine model for AMVP with bi-directional temporal prediction must sendtwo reference indices, two MVP indices, and either four or six MVDs,based on Affine motion model.

Disclosed is a system and method of reducing overhead of Bi-directionaltemporal prediction. The current approach in JVET and VVC signals MVinformation overhead twice resulting in two MVs that are independentfrom each other. The overhead or signaling two independent MVs can bereduced if the two MVs for bi-directional temporal prediction arerelated. When the two MVs are related (or paired), the second MV can befully or partially derived from the first MV and thus reducing theoverhead for the second MV.

The relationship between the MV pair (first MV and second MV) can besignificant for achieving high coding efficiency. There are manypossible ways to define a MV pair relationship. In some embodiments,optical flow can be assumed and/or that the first MV and second MV canhave similar trajectories can be assumed. In such an embodiment, thesecond MV can be considered a scaled version of the first MV and therelationship can be defined as follows:

MV2=((POC_Cur−POC_L1)/(POC_Cur−POC_L0))*MV1

-   -   Wherein:    -   MV1 and MV2 are MV of the first and second MV, respectively;    -   POC_Cur is the POC index of the current slice; and

POC_L0 and POC_L1 are the POC indices of the reference used by MV1 andMV2, respectively.

This equation shows an example of a derivation of the second MV in whichthe first MV of the MV pair uses a reference slice stored in one ofreference lists, such as reference list 0 (and or any other known,convenient and/or desired reference) and the second MV of the MV pairuses a reference slice stored in another list of reference lists (and orany other known, convenient and/or desired reference).

Additionally, there are many ways to signal the second MV with reducedoverhead based on the system in which the second MV is derived from thefirst MV. In some embodiments, the signaling scheme may not send areference index, MVP index and MVD of the second MV. In suchembodiments, a reference slice in list 1 can be determined to be usedfor the second MV—by way of non-limiting example, reference index 0 oflist 1 can be used. MV2 can thus be computed based on the equationprovided.

In some alternate embodiments, MV2 can be configured as the mirror ofMV1 and thus be derived or constructed from MV1.

In still further alternate embodiments, a reference index, absentsending an MVP index and MVD of the second MV can be established fromthe MV1 and MV2 information. In such alternate embodiments, the systemcan first determine a reference slice in list 1 of the second MV usingthe signaled reference index which can be literally signaled, thencompute MV2 according to the provided equation.

There are a few possible ways to utilize MV pair concept when the affinemotion model is employed. In some embodiments, a control point MV of thesecond list can be determined by scaling a corresponding control pointMV of the first list in accordance with the equation provided above. AMV of the second list for each sub-block within a coding block can thenbe computed based on the derived control point MV. In some alternateembodiments, a MV of the first list for each sub-block can be determinedusing signaled control point MVs, then a scaled MV of the first list canbe used to determine the MV of the second list for each sub-block.

In still further alternate embodiments, MVD2 can be related to MVD1where MVD1 and MVD2 are difference between motion vectors interrelatedin accordance with the following equation:

MVD2=((POC_Cur−POC_L1)/(POC_Cur−POC_L0))*MVD1

Thus, MVD2 can be derived or determined from MVD1 and the system cansend reference index information and an MVP index, but the MVD of thesecond MV need not be transmitted as it can be directly determined fromMVD1.

Furthermore, there are also many ways to add an MV pair (interrelatedMV1 and MV2) concept to the existing AMVP and affine bi-directionaltemporal prediction systems. In some embodiments, a new flag at CU levelcan be introduced to indicate whether an MV pair with reduced MV2overhead or the existing full MV2 overhead signaling is used. Inembodiments in which full MV2 overhead signaling is used, referenceindex, MVP index and MVD can be signaled as in current JVET and VVCsystems. In alternate embodiments, an MV pair option can be signaled asa special index of list 1—by way of non-limiting example, referenceindex 1 can be considered MV pair option with a reference slice set toindex 0 of list 1. Additionally, in some embodiments, this option can bedisabled for Generalized PB (GPB) slice, where all reference slices inlist 0 are identical to list 1, since MV1 and MV2 are identical based onthe provided equation.

FIG. 7 depicts a block diagram of a reduced-overhead encoding method 700for use in encoding video. In step 702 information related to a CU canbe received then in step 704 the information can be evaluated todetermine whether more than one MV is to be used in the coding process.If in step 704 it is determined that more than one MV is to be used inthe coding process, then the system can proceed to step 706 in which MV1(the first motion vector) and MV2 (the second motion vector) aredetermined. Then in step 708, a relationship between MV1 and MV2 can bedetermined, using any one or more of the previously described techniquesand/or any other known convenient and/or desired method and/ortechnique. However, in some embodiments, step 708 can precede step 706and the second motion vector can be defined directly by reference to thefirst motion vector. In step 710, signaling related to the relationshipbetween MV1 and MV2 can be determined, using any one or more of thepreviously described techniques and/or any other known convenient and/ordesired method and/or technique and then the CU can be encoded with therelevant information related to MV1 and the relationship to MV2 in step712 and the encoded bitstream can be transmitted in step 714. If in step704 it is determined that fewer than two MVs are desired for encoding,then the process can proceed directly from step 704 to the encoding step712 and then to transmission in step 714.

FIG. 8 depicts a block diagram of a reduced-overhead decoding method 800for use in decoding video. In step 802 a signal is received and then aCU is decoded in step 804. The in step 806 is determined whether morethan one MV is indicated in the received signal. If in step 806 it isdetermined that more than one MV is indicated in the received signal,then in step 808 MV1 is determined from signal and information regardingMV2 is determined from the signal. MV2 is then constructed from MV1 andthe information regarding MV2 in step 810. The reconstruction of MV2 canbe performed in accordance with any of the techniques and methodsdescribed herein and/or any other know, convenient and/or desiredtechnique and/or method. In step 812 the video can be reconstructed andthen can be displayed in step 814. If in step 806 is determined that oneor fewer MVs are indicated in the received signal, then the system canproceed from step 806 to reconstruction of the video in step 812 anddisplay in step 814.

The execution of the sequences of instructions required to practice theembodiments can be performed by a computer system 900 as shown in FIG.9. In an embodiment, execution of the sequences of instructions isperformed by a single computer system 900. According to otherembodiments, two or more computer systems 900 coupled by a communicationlink 915 can perform the sequence of instructions in coordination withone another. Although a description of only one computer system 900 willbe presented below, however, it should be understood that any number ofcomputer systems 900 can be employed to practice the embodiments.

A computer system 900 according to an embodiment will now be describedwith reference to FIG. 9, which is a block diagram of the functionalcomponents of a computer system 900. As used herein, the term computersystem 900 is broadly used to describe any computing device that canstore and independently run one or more programs.

Each computer system 900 can include a communication interface 914coupled to the bus 906. The communication interface 914 provides two-waycommunication between computer systems 900. The communication interface914 of a respective computer system 900 transmits and receiveselectrical, electromagnetic or optical signals, that include datastreams representing various types of signal information, e.g.,instructions, messages and data. A communication link 915 links onecomputer system 900 with another computer system 900. For example, thecommunication link 915 can be a LAN, in which case the communicationinterface 914 can be a LAN card, or the communication link 915 can be aPSTN, in which case the communication interface 914 can be an integratedservices digital network (ISDN) card or a modem, or the communicationlink 915 can be the Internet, in which case the communication interface914 can be a dial-up, cable or wireless modem.

A computer system 900 can transmit and receive messages, data, andinstructions, including program, i.e., application, code, through itsrespective communication link 915 and communication interface 914.Received program code can be executed by the respective processor(s) 907as it is received, and/or stored in the storage device 910, or otherassociated non-volatile media, for later execution.

In an embodiment, the computer system 900 operates in conjunction with adata storage system 931, e.g., a data storage system 931 that contains adatabase 932 that is readily accessible by the computer system 900. Thecomputer system 900 communicates with the data storage system 931through a data interface 933. A data interface 933, which is coupled tothe bus 906, transmits and receives electrical, electromagnetic oroptical signals, that include data streams representing various types ofsignal information, e.g., instructions, messages and data. Inembodiments, the functions of the data interface 933 can be performed bythe communication interface 914.

Computer system 900 includes a bus 906 or other communication mechanismfor communicating instructions, messages and data, collectively,information, and one or more processors 907 coupled with the bus 906 forprocessing information. Computer system 900 also includes a main memory908, such as a random access memory (RAM) or other dynamic storagedevice, coupled to the bus 906 for storing dynamic data and instructionsto be executed by the processor(s) 907. The main memory 908 also can beused for storing temporary data, i.e., variables, or other intermediateinformation during execution of instructions by the processor(s) 907.

The computer system 900 can further include a read only memory (ROM) 909or other static storage device coupled to the bus 906 for storing staticdata and instructions for the processor(s) 907. A storage device 910,such as a magnetic disk or optical disk, can also be provided andcoupled to the bus 906 for storing data and instructions for theprocessor(s) 907.

A computer system 900 can be coupled via the bus 906 to a display device911, such as, but not limited to, a cathode ray tube (CRT) or aliquid-crystal display (LCD) monitor, for displaying information to auser. An input device 912, e.g., alphanumeric and other keys, is coupledto the bus 906 for communicating information and command selections tothe processor(s) 907.

According to one embodiment, an individual computer system 900 performsspecific operations by their respective processor(s) 907 executing oneor more sequences of one or more instructions contained in the mainmemory 908. Such instructions can be read into the main memory 908 fromanother computer-usable medium, such as the ROM 909 or the storagedevice 910. Execution of the sequences of instructions contained in themain memory 908 causes the processor(s) 907 to perform the processesdescribed herein. In alternative embodiments, hard-wired circuitry canbe used in place of or in combination with software instructions. Thus,embodiments are not limited to any specific combination of hardwarecircuitry and/or software.

The term “computer-usable medium,” as used herein, refers to any mediumthat provides information or is usable by the processor(s) 907. Such amedium can take many forms, including, but not limited to, non-volatile,volatile and transmission media. Non-volatile media, i.e., media thatcan retain information in the absence of power, includes the ROM 909, CDROM, magnetic tape, and magnetic discs. Volatile media, i.e., media thatcan not retain information in the absence of power, includes the mainmemory 908. Transmission media includes coaxial cables, copper wire andfiber optics, including the wires that comprise the bus 906.Transmission media can also take the form of carrier waves; i.e.,electromagnetic waves that can be modulated, as in frequency, amplitudeor phase, to transmit information signals. Additionally, transmissionmedia can take the form of acoustic or light waves, such as thosegenerated during radio wave and infrared data communications.

In the foregoing specification, the embodiments have been described withreference to specific elements thereof. It will, however, be evidentthat various modifications and changes can be made thereto withoutdeparting from the broader spirit and scope of the embodiments. Forexample, the reader is to understand that the specific ordering andcombination of process actions shown in the process flow diagramsdescribed herein is merely illustrative, and that using different oradditional process actions, or a different combination or ordering ofprocess actions can be used to enact the embodiments. The specificationand drawings are, accordingly, to be regarded in an illustrative ratherthan restrictive sense.

It should also be noted that the present invention can be implemented ina variety of computer systems. The various techniques described hereincan be implemented in hardware or software, or a combination of both.Preferably, the techniques are implemented in computer programsexecuting on programmable computers that each include a processor, astorage medium readable by the processor (including volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device. Program code is applied to data enteredusing the input device to perform the functions described above and togenerate output information. The output information is applied to one ormore output devices. Each program is preferably implemented in a highlevel procedural or object oriented programming language to communicatewith a computer system. However, the programs can be implemented inassembly or machine language, if desired. In any case, the language canbe a compiled or interpreted language. Each such computer program ispreferably stored on a storage medium or device (e.g., ROM or magneticdisk) that is readable by a general or special purpose programmablecomputer for configuring and operating the computer when the storagemedium or device is read by the computer to perform the proceduresdescribed above. The system can also be considered to be implemented asa computer-readable storage medium, configured with a computer program,where the storage medium so configured causes a computer to operate in aspecific and predefined manner. Further, the storage elements of theexemplary computing applications can be relational or sequential (flatfile) type computing databases that are capable of storing data invarious combinations and configurations.

FIG. 10 is a high level view of a source device 1012 and destinationdevice 1010 that may incorporate features of the systems and devicesdescribed herein. As shown in FIG. 10, example video coding system 1010includes a source device 1012 and a destination device 1014 where, inthis example, the source device 1012 generates encoded video data.Accordingly, source device 1012 may be referred to as a video encodingdevice. Destination device 1014 may decode the encoded video datagenerated by source device 1012. Accordingly, destination device 1014may be referred to as a video decoding device. Source device 1012 anddestination device 1014 may be examples of video coding devices.

Destination device 1014 may receive encoded video data from sourcedevice 1012 via a channel 1016. Channel 1016 may comprise a type ofmedium or device capable of moving the encoded video data from sourcedevice 1012 to destination device 1014. In one example, channel 1016 maycomprise a communication medium that enables source device 1012 totransmit encoded video data directly to destination device 1014 inreal-time.

In this example, source device 1012 may modulate the encoded video dataaccording to a communication standard, such as a wireless communicationprotocol, and may transmit the modulated video data to destinationdevice 1014. The communication medium may comprise a wireless or wiredcommunication medium, such as a radio frequency (RF) spectrum or one ormore physical transmission lines. The communication medium may form partof a packet-based network, such as a local area network, a wide-areanetwork, or a global network such as the Internet. The communicationmedium may include routers, switches, base stations, or other equipmentthat facilitates communication from source device 1012 to destinationdevice 1014. In another example, channel 1016 may correspond to astorage medium that stores the encoded video data generated by sourcedevice 1012.

In the example of FIG. 10, source device 1012 includes a video source1018, video encoder 1020, and an output interface 1022. In some cases,output interface 1028 may include a modulator/demodulator (modem) and/ora transmitter. In source device 1012, video source 1018 may include asource such as a video capture device, e.g., a video camera, a videoarchive containing previously captured video data, a video feedinterface to receive video data from a video content provider, and/or acomputer graphics system for generating video data, or a combination ofsuch sources.

Video encoder 1020 may encode the captured, pre-captured, orcomputer-generated video data. An input image may be received by thevideo encoder 1020 and stored in the input frame memory 1021. Thegeneral purpose processor 1023 may load information from here andperform encoding. The program for driving the general purpose processormay be loaded from a storage device, such as the example memory modulesdepicted in FIG. 10. The general purpose processor may use processingmemory 1022 to perform the encoding, and the output of the encodinginformation by the general processor may be stored in a buffer, such asoutput buffer 1026.

The video encoder 1020 may include a resampling module 1025 which may beconfigured to code (e.g., encode) video data in a scalable video codingscheme that defines at least one base layer and at least one enhancementlayer. Resampling module 1025 may resample at least some video data aspart of an encoding process, wherein resampling may be performed in anadaptive manner using resampling filters.

The encoded video data, e.g., a coded bit stream, may be transmitteddirectly to destination device 1014 via output interface 1028 of sourcedevice 1012. In the example of FIG. 10, destination device 1014 includesan input interface 1038, a video decoder 1030, and a display device1032. In some cases, input interface 1028 may include a receiver and/ora modem. Input interface 1038 of destination device 1014 receivesencoded video data over channel 1016. The encoded video data may includea variety of syntax elements generated by video encoder 1020 thatrepresent the video data. Such syntax elements may be included with theencoded video data transmitted on a communication medium, stored on astorage medium, or stored a file server.

The encoded video data may also be stored onto a storage medium or afile server for later access by destination device 1014 for decodingand/or playback. For example, the coded bitstream may be temporarilystored in the input buffer 1031, then loaded in to the general purposeprocessor 1033. The program for driving the general purpose processormay be loaded from a storage device or memory. The general purposeprocessor may use a process memory 1032 to perform the decoding. Thevideo decoder 1030 may also include a resampling module 1035 similar tothe resampling module 1025 employed in the video encoder 1020.

FIG. 10 depicts the resampling module 1035 separately from the generalpurpose processor 1033, but it would be appreciated by one of skill inthe art that the resampling function may be performed by a programexecuted by the general purpose processor, and the processing in thevideo encoder may be accomplished using one or more processors. Thedecoded image(s) may be stored in the output frame buffer 1036 and thensent out to the input interface 1038.

Display device 1038 may be integrated with or may be external todestination device 1014. In some examples, destination device 1014 mayinclude an integrated display device and may also be configured tointerface with an external display device. In other examples,destination device 1014 may be a display device. In general, displaydevice 1038 displays the decoded video data to a user.

Video encoder 1020 and video decoder 1030 may operate according to avideo compression standard. ITU-T VCEG (Q6/16) and ISO/IEC MPEG (JTC1/SC 29/WG 11) are studying the potential need for standardization offuture video coding technology with a compression capability thatsignificantly exceeds that of the current High Efficiency Video CodingHEVC standard (including its current extensions and near-term extensionsfor screen content coding and high-dynamic-range coding). The groups areworking together on this exploration activity in a joint collaborationeffort known as the Joint Video Exploration Team (WET) to evaluatecompression technology designs proposed by their experts in this area. Arecent capture of WET development is described in the “AlgorithmDescription of Joint Exploration Test Model 5 (JEM 5)”, JVET-E1001-V2,authored by J. Chen, E. Alshina, G. Sullivan, J. Ohm, J. Boyce.

Additionally or alternatively, video encoder 1020 and video decoder 1030may operate according to other proprietary or industry standards thatfunction with the disclosed JVET features. Thus, other standards such asthe ITU-T H.264 standard, alternatively referred to as MPEG-4, Part 10,Advanced Video Coding (AVC), or extensions of such standards. Thus,while newly developed for JVET, techniques of this disclosure are notlimited to any particular coding standard or technique. Other examplesof video compression standards and techniques include MPEG-2, ITU-TH.263 and proprietary or open source compression formats and relatedformats.

Video encoder 1020 and video decoder 1030 may be implemented inhardware, software, firmware or any combination thereof. For example,the video encoder 1020 and decoder 1030 may employ one or moreprocessors, digital signal processors (DSPs), application specificintegrated circuits (ASICs), field programmable gate arrays (FPGAs),discrete logic, or any combinations thereof. When the video encoder 1020and decoder 1030 are implemented partially in software, a device maystore instructions for the software in a suitable, non-transitorycomputer-readable storage medium and may execute the instructions inhardware using one or more processors to perform the techniques of thisdisclosure. Each of video encoder 1020 and video decoder 1030 may beincluded in one or more encoders or decoders, either of which may beintegrated as part of a combined encoder/decoder (CODEC) in a respectivedevice.

Aspects of the subject matter described herein may be described in thegeneral context of computer-executable instructions, such as programmodules, being executed by a computer, such as the general-purposeprocessors 1023 and 1033 described above. Generally, program modulesinclude routines, programs, objects, components, data structures, and soforth, which perform particular tasks or implement particular abstractdata types. Aspects of the subject matter described herein may also bepracticed in distributed computing environments where tasks areperformed by remote processing devices that are linked through acommunications network. In a distributed computing environment, programmodules may be located in both local and remote computer storage mediaincluding memory storage devices.

Examples of memory include random access memory (RAM), read only memory(ROM), or both. Memory may store instructions, such as source code orbinary code, for performing the techniques described above. Memory mayalso be used for storing variables or other intermediate informationduring execution of instructions to be executed by a processor, such asprocessor 1023 and 1033.

A storage device may also store instructions, instructions, such assource code or binary code, for performing the techniques describedabove. A storage device may additionally store data used and manipulatedby the computer processor. For example, a storage device in a videoencoder 1020 or a video decoder 1030 may be a database that is accessedby computer system 1023 or 1033. Other examples of storage deviceinclude random access memory (RAM), read only memory (ROM), a harddrive, a magnetic disk, an optical disk, a CD-ROM, a DVD, a flashmemory, a USB memory card, or any other medium from which a computer canread.

A memory or storage device may be an example of a non-transitorycomputer-readable storage medium for use by or in connection with thevideo encoder and/or decoder. The non-transitory computer-readablestorage medium contains instructions for controlling a computer systemto be configured to perform functions described by particularembodiments. The instructions, when executed by one or more computerprocessors, may be configured to perform that which is described inparticular embodiments.

Also, it is noted that some embodiments have been described as a processwhich can be depicted as a flow diagram or block diagram. Although eachmay describe the operations as a sequential process, many of theoperations can be performed in parallel or concurrently. In addition,the order of the operations may be rearranged. A process may haveadditional steps not included in the figures.

Particular embodiments may be implemented in a non-transitorycomputer-readable storage medium for use by or in connection with theinstruction execution system, apparatus, system, or machine. Thecomputer-readable storage medium contains instructions for controlling acomputer system to perform a method described by particular embodiments.The computer system may include one or more computing devices. Theinstructions, when executed by one or more computer processors, may beconfigured to perform that which is described in particular embodiments

As used in the description herein and throughout the claims that follow,“a”, “an”, and “the” includes plural references unless the contextclearly dictates otherwise. Also, as used in the description herein andthroughout the claims that follow, the meaning of “in” includes “in” and“on” unless the context clearly dictates otherwise.

Although exemplary embodiments of the invention have been described indetail and in language specific to structural features and/ormethodological acts above, it is to be understood that those skilled inthe art will readily appreciate that many additional modifications arepossible in the exemplary embodiments without materially departing fromthe novel teachings and advantages of the invention. Moreover, it is tobe understood that the subject matter defined in the appended claims isnot necessarily limited to the specific features or acts describedabove. Accordingly, these and all such modifications are intended to beincluded within the scope of this invention construed in breadth andscope in accordance with the appended claims.

1. A system for decoding video comprising: (a) receiving a bitstream ofencoded video; (b) decoding said bitstream of said encoded video; (c)determining a coding unit within said decoded bitstream; (d) determiningmotion information associated with said coding unit; (e) determiningwhether more than one motion vector is associated with said motioninformation; (f) modifying at least one of a first motion vector and asecond motion vector if it is determined that said motion information isassociated with more than one motion vector; (g) decoding said codingunit based upon said modified said at least one of said first motionvector and said second motion vector.
 2. The system for decoding videoof claim 1 wherein said motion information comprises informationsufficient to reconstruct a MVP index and a MVD of said second motionvector.
 3. The system for decoding video of claim 1 wherein said motioninformation includes a scaling factor.
 4. The system for decoding videoof claim 3 wherein said motion information comprises informationsufficient to reconstruct a MVP index and a MVD of said second motionvector.
 5. The system for decoding video of claim 1 wherein said motioninformation comprises information regarding a reference slice.
 6. Thesystem for decoding video of claim 5 wherein said motion informationcomprises information sufficient to reconstruct a MVP index and a MVD ofsaid second motion vector.
 7. The system for decoding video of claim 1wherein said motion information indicates said second motion vector is amirror image of said first motion vector.
 8. The system for decodingvideo of claim 7 wherein said motion information comprises informationsufficient to reconstruct a MVP index and a MVD of said second motionvector.
 9. The system for decoding video of claim 1 wherein said motioninformation comprises reference index information.
 10. The system fordecoding video of claim 9 wherein said motion information comprisesinformation sufficient to reconstruct a MVP index and a MVD of saidsecond motion vector.
 11. The system for decoding video of claim 1wherein said motion information comprises a control point for saidsecond motion vector.
 12. The system for decoding video of claim 11wherein said motion information comprises information sufficient toreconstruct a MVP index and a MVD of said second motion vector.
 13. Thesystem for decoding video of claim 11 wherein said motion informationcomprises information sufficient to reconstruct an MVP index and aplurality of MVDs associated with said second motion vector.
 14. Thesystem for decoding video of claim 1 wherein said coding unit is part ofa bi-directionally predicted coding unit.
 15. The system for decodingvideo of claim 14 further comprising said modifying said first motionvector and said second motion vector if it is determined that saidmotion information is associated with more than one motion vector.
 16. Amethod of decoding a video included in a bitstream comprising: (a)receiving a coding unit included in a B-slice of a current frame of saidvideo; (b) receiving a first motion vector associated with said codingunit of said B-slice of said current frame of said video referencing atemporally previous reference slice of a temporally previous referenceframe relative to said current frame of said coding unit; (c) receivinga second motion vector associated with said coding unit of said B-sliceof said current frame of said video referencing a temporally futurereference slice of a temporally future frame relative to said currentframe of said coding unit; (d) modifying at least one of said firstmotion vector and said second motion vector based at least in part uponthe other of said at least one of said first motion vector and saidsecond motion vector and based upon an optical flow of said temporallyprevious reference slice and said temporally future reference slice; (e)decoding said coding unit based upon said modified at least one of saidfirst motion together with said temporally previous reference slice ofsaid temporally previous frame and said second motion vector togetherwith said temporally future reference slice of said temporally futureframe.
 17. The method of decoding of claim 16 wherein said modifyingcomprises information sufficient to reconstruct an MVP index and an MVDof said second motion vector.
 18. The method of decoding of claim 16wherein said modifying comprises a scaling factor.
 19. The method ofdecoding of claim 16 wherein said modifying comprises said second motionvector is a mirror image of said first motion vector.